Data Engineer II, Sales Data Services (SDS)
Amazon· Research Science
About this role
Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high-quality sites across the web, and on millions of Kindles, tablets, and mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.
SDS is part of the Sales Intelligence, Technology, & Enablement organization (SITE). We are a big-data focused engineering team that provides unique, pan-Amazon datasets consolidating advertiser, seller, and vendor KPIs, exposed via data warehousing , fast APIs and agentic soutions. Our data platform is designed to serve Sales teams across WW Advertising orgs for various applications including business processes, ML, account management, marketing, and decisioning systems.
Key job responsibilities
• Design, implement, and support data warehouse data lake infrastructure using AWS big data stack, Python, Redshift.
• Develop and manage ETLs to source data from various data lakes and create unified data model for analytics and reporting
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary collaborate across teams to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.
A day in the life
You will work closely with the Business Intelligence Engineers, Data Scientists, Product Managers, Software Development teams and other business stakeholders on many unique business problems and use creative problem solving to deliver actionable output in data gathering, transformation, ingestion and storage. You should be able to gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. As a DE, you will be regularly mentoring junior engineerings, developing technical your leadership, and contributing to the design and implementation of highly available, scalable, stable, secure, and cost-effective analytic solutions.
About the team
Sales Data Services team is part of Sales AI, a central data and science organization within Sales Intelligence, Technology, & Enablement organization (SITE) that powers Ad Sales selling motions and workflows via a suite of AI/ML services. Sales AI’s mission is to equip Sales with the data- and science-backed intelligence they need (and when they need it) to improve their selling motions from routine practices to peak performance.
SDS is part of the Sales Intelligence, Technology, & Enablement organization (SITE). We are a big-data focused engineering team that provides unique, pan-Amazon datasets consolidating advertiser, seller, and vendor KPIs, exposed via data warehousing , fast APIs and agentic soutions. Our data platform is designed to serve Sales teams across WW Advertising orgs for various applications including business processes, ML, account management, marketing, and decisioning systems.
Key job responsibilities
• Design, implement, and support data warehouse data lake infrastructure using AWS big data stack, Python, Redshift.
• Develop and manage ETLs to source data from various data lakes and create unified data model for analytics and reporting
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary collaborate across teams to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.
A day in the life
You will work closely with the Business Intelligence Engineers, Data Scientists, Product Managers, Software Development teams and other business stakeholders on many unique business problems and use creative problem solving to deliver actionable output in data gathering, transformation, ingestion and storage. You should be able to gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. As a DE, you will be regularly mentoring junior engineerings, developing technical your leadership, and contributing to the design and implementation of highly available, scalable, stable, secure, and cost-effective analytic solutions.
About the team
Sales Data Services team is part of Sales AI, a central data and science organization within Sales Intelligence, Technology, & Enablement organization (SITE) that powers Ad Sales selling motions and workflows via a suite of AI/ML services. Sales AI’s mission is to equip Sales with the data- and science-backed intelligence they need (and when they need it) to improve their selling motions from routine practices to peak performance.
Basic qualifications
- 3+ years of data engineering experience
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Preferred qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Frequently Asked Questions
Is the salary disclosed for the Data Engineer II, Sales Data Services (SDS) position at Amazon?
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Where is the Data Engineer II, Sales Data Services (SDS) position at Amazon located?
This Data Engineer II, Sales Data Services (SDS) role at Amazon is based in Bengaluru, Karnataka, IND. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the Data Engineer II, Sales Data Services (SDS) role at Amazon full-time or part-time?
This is listed as a full time position. It is posted as a Data Engineer II, Sales Data Services (SDS) role in the Research Science department at Amazon.
Which team or department does the Data Engineer II, Sales Data Services (SDS) at Amazon belong to?
This Data Engineer II, Sales Data Services (SDS) position is part of the Research Science department at Amazon. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Data Engineer II, Sales Data Services (SDS) position at Amazon?
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When was the Data Engineer II, Sales Data Services (SDS) job at Amazon posted?
This Data Engineer II, Sales Data Services (SDS) position at Amazon was posted on Jul 13, 2026. Apply as soon as possible — early applications are often reviewed first.
Data Engineer II, Sales Data Services (SDS)
Amazon
You'll be redirected to Amazon's official application page on amazonjobs.